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Field
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Eligibility criteria Selection will be based on the following scientific and technical criteria: • PhD in computational biology, machine learning, bioinformatics or a related field. • Proficiency with Python
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and economy that respect people and their environment. We are looking for our next postdoctoral researcher in computer graphics and machine learning to join the Image, Data and Signal (IDS) department
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in privacy preserving machine learning (ML) within the SSF-ML-DH project, under the supervision of Olivier Cappé (CNRS, DI ENS) and Jamal Atif (Ecole Polytechnique, CMAP). Funding is available for two
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, clinical, structural bioinformatics data, which should be outlined in the CV Prior experience in large-scale data processing and statistics / machine learning is required Demonstrated skills and knowledge in
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The Machine Learning for Integrative Genomics team (https://research.pasteur.fr/en/team/machine-learning-for-integrative- genomics/) at Institut Pasteur, headed by Laura Cantini, works at
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) / InP contact layer (200 nm) / Si substrate The objective of the project is to develop a plasma etching process for this multilayer stack, enabling selective etch stopping on the InP contact layer, which
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decision making are intertwined processes in many everyday situations. One example is when you decide where to have lunch: should you go to the nearby coffee shop or to the university cafeteria? Learning
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in the framework of the BBEST PEPR. The project aims to valorise syngas derived from biomass via the OX-ZEO process. This relay catalytic process combines a hydrogenating metal oxide to produce
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-based fiber panels are generally produced using a dry process and require the addition of heat- fusible synthetic polymer fibers to ensure mechanical strength during handling and dimensional stability in
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mixtures, including information retrieval, random access, approximate search, querying and filtering, encryption, compression, and many other information-processing tasks. Our team is looking for a talented